MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks.
MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks.
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DOI：
10.1093/nar/gkq312
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发表时间：
2010-07
影响因子：
14.9
通讯作者：
Jourdan F
中科院分区：
文献类型：
--
作者：
Cottret L;Wildridge D;Vinson F;Barrett MP;Charles H;Sagot MF;Jourdan F
高通量代谢组学实验旨在鉴定并最终定量生物系统中存在的所有代谢物。代谢物通过代谢反应相互联系，通常分为代谢途径。经典的代谢图谱提供了一个相关的背景，以帮助解释代谢组学实验和广泛的工具已经开发出来，以帮助在代谢途径中的代谢物。然而，在分离的断开通路内的代谢物的表示忽略了代谢物组的大部分连接性。根据定义，参考途径不能整合新的途径，也不能显示可能由共同邻居连接的代谢物之间的关系，而不被视为经典生化途径的联合成员。MetExplore是一个网络服务器，可以在基因组规模重建的代谢网络背景下将非靶向代谢组学实验中识别的代谢物联系起来。分析管道包括将代谢组学数据映射到生物体的特定代谢网络上，然后应用基于图形的方法和先进的可视化工具来增强数据分析。MetExplore Web服务器可在http://metexplore.toulouse.inra.fr上免费访问。
High-throughput metabolomic experiments aim at identifying and ultimately quantifying all metabolites present in biological systems. The metabolites are interconnected through metabolic reactions, generally grouped into metabolic pathways. Classical metabolic maps provide a relational context to help interpret metabolomics experiments and a wide range of tools have been developed to help place metabolites within metabolic pathways. However, the representation of metabolites within separate disconnected pathways overlooks most of the connectivity of the metabolome. By definition, reference pathways cannot integrate novel pathways nor show relationships between metabolites that may be linked by common neighbours without being considered as joint members of a classical biochemical pathway. MetExplore is a web server that offers the possibility to link metabolites identified in untargeted metabolomics experiments within the context of genome-scale reconstructed metabolic networks. The analysis pipeline comprises mapping metabolomics data onto the specific metabolic network of an organism, then applying graph-based methods and advanced visualization tools to enhance data analysis. The MetExplore web server is freely accessible at http://metexplore.toulouse.inra.fr.
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影响因子：
14.9
作者：
Wishart DS;Knox C;Guo AC;Eisner R;Young N;Gautam B;Hau DD;Psychogios N;Dong E;Bouatra S;Mandal R;Sinelnikov I;Xia J;Jia L;Cruz JA;Lim E;Sobsey CA;Shrivastava S;Huang P;Liu P;Fang L;Peng J;Fradette R;Cheng D;Tzur D;Clements M;Lewis A;De Souza A;Zuniga A;Dawe M;Xiong Y;Clive D;Greiner R;Nazyrova A;Shaykhutdinov R;Li L;Vogel HJ;Forsythe I
通讯作者：
Forsythe I
影响因子：
14.9
作者：
Caspi R;Altman T;Dale JM;Dreher K;Fulcher CA;Gilham F;Kaipa P;Karthikeyan AS;Kothari A;Krummenacker M;Latendresse M;Mueller LA;Paley S;Popescu L;Pujar A;Shearer AG;Zhang P;Karp PD
通讯作者：
Karp PD
影响因子：
3.6
作者：
Jourdan, Fabien;Cottret, Ludovic;Huc, Laurence;Wildridge, David;Scheltema, Richard;Hillenweck, Anne;Barrett, Michael P.;Zalko, Daniel;Watson, David G.;Debrauwer, Laurent
通讯作者：
Debrauwer, Laurent
影响因子：
14.9
作者：
Paley, Suzanne M.;Karp, Peter D.
通讯作者：
Karp, Peter D.
影响因子：
7
作者：
Yeh, W;Hanekamp, T;Altman, RB
通讯作者：
Altman, RB